// but file "b" is not stale yet. Thus, once the pruning thread wakes up (in
  // one second of wall time), it should remove "a" and leave "b" alone.
  uint64 start = Env::Default()->NowSeconds();
  do {
    Env::Default()->SleepForMicroseconds(100000);
  } while (cache.CacheSize() == 24 && Env::Default()->NowSeconds() - start < 3);
  // There should be one block left in the cache, and it should be the first
  // block of "b".

  size_t finish = block_size_ * ((offset + n) / block_size_);
  if (finish < offset + n) {
    finish += block_size_;
  }
  size_t total_bytes_transferred = 0;
  // Now iterate through the blocks, reading them one at a time.
  for (size_t pos = start; pos < finish; pos += block_size_) {
    Key key = std::make_pair(filename, pos);
    // Look up the block, fetching and inserting it if necessary, and update the

  }
  return absl::OkStatus();
}

// TODO(agarwal): use an automatic mechanism for handling None arguments to
// gradient functions.
//
// Some gradient functions can accept None arguments for gradients. The
// following maps the operation name to the indices at which the corresponding
// gradient function can accept None values. e.g. FusedBatchNorm outputs 5
// values and hence receives 5 gradient values during backprop. However the

    url_lines = result_store_links.setdefault(url, {})
    # Each bazel RBE invocation should produce two
    # 'Streaming build results to: ...' lines, one at the start, and one at the
    # end of the invocation.
    # If there's a failure message, it will be found in-between these two.

    if not current_url:
      url_lines['start'] = i
    elif current_url == url:
      url_lines['end'] = i
    else:

**Raspberry Pi 2 and 3**      | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.html)           | [Py3](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp34-none-linux_armv7l.whl)

      # it, and print that list for debugging. Not really clear if this is
      # helpful since the only examples I've seen are enormous.
      bazel query "rdeps(kind(py_test, $(cat $BATS_TEST_TMPDIR/deps)), $dep, 1)"
    done < $BATS_TEST_TMPDIR/missing_deps
    exit 1
  fi
}

# The Python package is not allowed to depend on any CUDA packages.
@test "Pip package doesn't depend on CUDA" {
  bazel cquery \

// that shares the underlying buffer. Otherwise, it currently requires at least
// one of the source or destination devices to be CPU (i.e., for the source or
// destination tensor to be placed in host memory).
// If async execution is enabled, the copy may be enqueued and the call will
// return "non-ready" handle. Else, this function returns after the copy has
// been done.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_TensorHandleCopyToDevice(

    airtime before a decision is made regarding whether they are to be migrated
    to the core.
*   As every PR requires several CPU/GPU hours of CI testing, we discourage
    submitting PRs to fix one typo, one warning,etc. We recommend fixing the
    same issue at the file level at least (e.g.: fix all typos in a file, fix
    all compiler warnings in a file, etc.)
*   Tests should follow the

  std::unique_ptr<TFE_TensorHandle, decltype(&TFE_DeleteTensorHandle)> one(
      TestScalarTensorHandle(context.get(), 111.f), TFE_DeleteTensorHandle);
  op.reset(TFE_NewOp(context.get(), "AssignVariableOp", status.get()));
  TFE_OpSetAttrType(op.get(), "dtype", TF_FLOAT);
  TFE_OpAddInput(op.get(), var_handle, status.get());
  TFE_OpAddInput(op.get(), one.get(), status.get());
  TFE_OpSetDevice(op.get(), name, status.get());

    TF_Status* status);

// -----------------------------------------------------------------------------
// Eager Executor APIs.
typedef struct TFE_Executor TFE_Executor;

// Creates a new eager Executor. Nodes in one executor are guaranteed to be
// executed in sequence. Assigning nodes to different executors allows executing
// nodes in parallel.
// in_flight_nodes_limit: when is_async is true, this value controls the